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## Markov Processes In the mechanics of random motion, Markov processes are responsible for the kinematics. In Section 4.1, we first introduce the Markov processes, which are a powerful tool in the study of the mechanics of random motion, and show that Markov processes determine semigroups of operators. In Section 4.2, we describe the transformation of a probability measure by a multiplicative functional, and we prove the Kac and Maruyama-Girsanov formulas. In Section 4.3, we show that changing the time scale alters the severity of randomness. In Section 4.4 we discuss the duality and time reversal of Markov processes. In Section 4.5 we define the "terminal time" and explain time reversal from the terminal time. Finally, in Section 4.6, we discuss the time reversal of the random motion governed by the equations of motion. ## Time-Homogeneous Markov Proces-ses Consider a particle that moves in a certain space S, called a state space. For example, S can be the d-dimensional Euclidean space R d . Calling S "state space" is just a custom in the theory of Markov processes; the term "state" has no particular meaning. A Markov process evolving in the state space S is denoted by {X t , t ≥
- Author
- Masao Nagasawa; Springer Nature
- Publisher
- Springer International Publishing AG
- Published
- 2021
- Language
- EN
- ISBN
- 9783030626877
- Subjects
- Mathematics, Science, Physics
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